code: def create_tf_model(
      features, layers, units, device, input_name, output_name
  ):
      with tf.device(device):
          x = tf.placeholder(
              tf.float32, shape=[None, features], name=input_name
          )
          y = x
          for i in range(layers):
              W = tf.Variable(
                  tf.random_normal(
                      [features if y == x else units, units]
                  )
              )
              b = tf.Variable(tf.zeros([units]))
              y = tf.tanh(
                  tf.matmul(y, W) + b,
                  name=output_name if i == layers - 1 else None,
              )
      return x, y
  
file_path: tfdeploy/tests/perf/measure_runtimes.py
imports: import os
  import time
  import json
  import uuid
  import itertools
  import collections
  import numpy
  import tensorflow
  import tfdeploy
label_desc: Use image node_id 1 for calling a global function with example usage: create_tf_model(features, layers, units, device, input_name, output_name) and returns: x,  y